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Summary

For algebra-based Introductory Statistics Courses.This very popular text is written to promote student success while maintaining the statistical integrity of the course. The author draws on his teaching experience and background in statistics and mathematics to achieve this balance. Three fundamental objectives motivate this text: (1) to generate and maintain student interest, thereby promoting student success and confidence; (2) to provide extensive and effective opportunity for student practice; (3) Allowing for flexibility of teaching styles. Datasets and other resources (where applicable) for this book are available here .

Table of Contents

Preface to the Instructor

xi

Student Resources

xxi

List of Applications

xxiii

Photo Credits

xxix

Part I: Getting the Information You Need

1

(58)

Data Collection

2

(57)

Introduction to the Practice of Statistics

3

(10)

Observational Studies, Experiments, and Simple Random Sampling

13

(10)

Other Effective Sampling Methods

23

(10)

Sources of Error in Sampling

33

(7)

The Design of Experiments

40

(19)

Chapter Review

52

(4)

Case Study: Chrysalises for Cash

56

(3)

Part II: Descriptive Statistics

59

(190)

Organizing and Summarizing Data

60

(60)

Organizing Qualitative Data

61

(16)

Organizing Quantitative Data: The Popular Displays

77

(20)

Additional Displays of Quantitative Data

97

(7)

Graphical Misrepresentations of Data

104

(16)

Chapter Review

110

(8)

Case Study: The Day the Sky Roared

118

(2)

Numerically Summarizing Data

120

(74)

Measures of Central Tendency

121

(16)

Measures of Dispersion

137

(20)

Measures of Central Tendency and Dispersion from Grouped Data

157

(8)

Measures of Position

165

(10)

The Five-Number Summary and Boxplots

175

(19)

Chapter Review

184

(7)

Case Study: Who Was `A Mourner'?

191

(3)

Describing the Relation between Two Variables

194

(55)

Scatter Diagrams and Correlation

195

(17)

Least-Squares Regression

212

(14)

Diagnostics on the Least-Squares Regression Line

226

Nonlinear Regression: Transformations (On CD)

1

(248)

Chapter Review

241

(6)

Case Study: Thomas Malthus, Population, and Subsistence

247

(2)

Part III: Probability and Probability Distributions

249

(166)

Probability

250

(64)

Probability Rules

251

(15)

The Addition Rule and Complements

266

(11)

Independence and the Multiplication Rule

277

(6)

Conditional Probability and the General Multiplication Rule

283

(10)

Counting Techniques

293

Bayes's Rule (ON CD)

1

(313)

Chapter Review

307

(5)

Case Study: The Case of the Body in the Bag

312

(2)

Discrete Probability Distributions

314

(44)

Discrete Random Variables

315

(13)

The Binomial Probability Distribution

328

(17)

The Poisson Probability Distribution

345

The Hypergeometric Probability Distribution (ON CD)

1

(357)

Chapter Review

352

(4)

Case Study: The Voyage of the St. Andrew

356

(2)

The Normal Probability Distribution

358

(57)

Properties of the Normal Distribution

359

(12)

The Standard Normal Distribution

371

(14)

Applications of the Normal Distribution

385

(9)

Assessing Normality

394

(8)

The Normal Approximation to the Binomial Probability Distribution

402

(13)

Chapter Review

407

(5)

Case Study: A Tale of Blood, Chemistry, and Health

412

(3)

Part IV: Inference: From Samples to Population

415

Sampling Distributions

416

(30)

Distribution of the Sample Mean

417

(17)

Distribution of the Sample Proportion

434

(12)

Chapter Review

442

(2)

Case Study: Sampling Distribution of the Median

444

(2)

Estimating the Value of a Parameter Using Confidence Intervals

446

(58)

The Logic in Constructing Confidence Intervals about a Population Mean Where the Population Standard Deviation is Known

447

(19)

Confidence Intervals about a Population Mean in Practice Where the Population Standard Deviation is Unknown

466

(12)

Confidence Intervals about a Population Proportion

478

(8)

Confidence Intervals about a Population Standard Deviation

486

(7)

Putting It All Together: Which Method Do I Use?

493

(11)

Chapter Review

497

(5)

Case Study: The Search for a Fire-Safe Cigarette

502

(2)

Testing Claims Regarding a Parameter

504

(70)

The Language of Hypothesis Testing

505

(8)

Testing Claims about a Population Mean Assuming the Population Standard Deviation Is Known

513

(18)

Testing Claims about a Population Mean in Practice

531

(13)

Testing Claims about a Population Proportion

544

(9)

Testing Claims about a Population Standard Deviation

553

(5)

Putting It All Together: Which Method Do I Use?

558

(3)

The Probability of a Type II Error and the Power of the Test

561

(13)

Chapter Review

567

(4)

Case Study: How Old Is Stonehenge?

571

(3)

Inference on Two Samples

574

(56)

Inference about Two Means: Dependent Samples

575

(13)

Inference about Two Means: Independent Samples

588

(13)

Inference about Two Population Proportions

601

(11)

Inference about Two Population Standard Deviations

612

(18)

Chapter Review

623

(5)

Case Study: Control in the Design of an Experiment

628

(2)

Inference on Categorical Data

630

(46)

Goodness of Fit Test

631

(10)

Contingency Tables and Association

641

(10)

Tests for Independence and the Homogeneity of Proportions

651

(25)

Chapter Review

668

(6)

Case Study: Feeling Lucky? Well, Are You?

674

(2)

Comparing Three or More Means

676

(60)

Comparing Three or More Means (One-Way Analysis of Variance)

677

(14)

Post-Hoc Tests on One-Way Analysis of Variance

691

(10)

The Randomized Complete Block Design

701

(10)

Two-Way Analysis of Variance

711

(25)

Chapter Review

728

(6)

Case Study: Hat Size and Intelligence

734

(2)

Inference on the Least-Squares Regression Model and Multiple Regression

736

Testing the Significance of the Least-Squares Regression Model

737

(16)

Confidence and Prediction Intervals

753

(5)

Multiple Regression

758

Chapter Review

783

(5)

Case Study: Housing Boom

788

Nonparametrics (ON CD)

An Overview of Nonparametric Statistics

Runs Test for Randomness

Inferences about Measures of Central Tendency

Inferences about the Difference between Two Medians: Dependent Samples

Inferences about the Difference between Two Medians: Independent Samples